Lung cancer is the greatest single cause of cancer mortality worldwide. Although environmental risk factors have been well defined, smoking prevalence has not declined. Available screening tests for early detection of lung cancer have not lowered overall morbidity and mortality from lung cancer. With the completion of the prototype sequence by the Human Genome Project, information on single nucleotide polymorphisms (SNPs) encoded in cytokine genes has become available. In particular, cytokine gene polymorphisms (CGPs) have recently been shown to be promising predictive markers in several solid tumor model systems and in stem cell transplantation. In the lung cancer model, we hypothesize that CGPs interact with inflammatory stimuli, including tobacco or asbestos exposure, to promote progression to lung cancer. If CGPs modulate risk of lung cancer, then screening tools can be developed to assess cancer risk and to detect high-risk patients. If CGPs correlate with outcome of lung cancer therapy, then the use of CGPs to predict response to therapy and guide clinical interventions may be feasible. These hypotheses are eminently testable in large clinical populations of cancer patients and controls for whom extensive clinical and phenotype data is available. To this end, we propose to collaborate with the CARET trial repository (NIH grant CA63673) to access blood samples from lung cancer patients and cancer-free individuals. Our application is an R21 exploratory project in response to PA-01-015 in which we will develop PCR arrays and retrospectively characterize 1,212 study individuals for a panel of 20 CGPs (Specific Aim 1). We will determine whether certain SNPs correlate with the presence of lung cancer (Specific Aim 2), and whether certain SNPs are associated with survival among lung cancer patients (Specific Aim 3). The information will be highly relevant to the design of larger confirmatory clinical studies in the future. Furthermore, the array methodology can be directly and immediately translated to high-throughput population-based testing. If CGPs can be identified as predictive risk markers or prognostic markers in lung cancer, then screening methods can be developed to screen for high-risk individuals before the development of lung cancer; furthermore, if SNPs correlate with clinical response, then use of SNPs genotyping to guide therapeutic interventions can be incorporated into the management care plan of the patient.